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Plasma metabolomic profile in prostatic intraepithelial neoplasia and prostate cancer and associations with the prostate-specific antigen and the Gleason score

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Abstract

Introduction

The metabolic alterations reflecting the influence of prostate cancer cells can be captured through metabolomic profiling.

Objective

To characterize the plasma metabolomic profile in prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa).

Methods

Metabolomics analyses were performed in plasma samples from individuals classified as non-cancerous control (n = 36), with PIN (n = 16), or PCa (n = 27). Untargeted [26 moieties identified after pre-processing by gas chromatography/mass spectrometry (GC/MS)] and targeted [46 amino acids, carbohydrates, organic acids and fatty acids by GC/MS, and 16 nucleosides and amino acids by ultra performance liquid chromatography-triple quadrupole/mass spectrometry (UPLC-TQ/MS)] analyses were performed. Prostate specific antigen (PSA) concentrations were measured in all samples. In PCa patients, the Gleason scores were determined.

Results

The metabolites that were best discriminated (p < 0.05, FDR < 0.2) for the Kruskal–Wallis test with Dunn’s post-hoc comparing the control versus the PIN and PCa groups included isoleucine, serine, threonine, cysteine, sarcosine, glyceric acid, among several others. PIN was mainly characterized by alterations on steroidogenesis, glycine and serine metabolism, methionine metabolism and arachidonic acid metabolism, among others. In the case of PCa, the most predominant metabolic alterations were ubiquinone biosynthesis, catecholamine biosynthesis, thyroid hormone synthesis, porphyrin and purine metabolism. In addition, we identified metabolites that were correlated to the PSA [i.e. hypoxanthine (r = − 0.60, p < 0.05; r = − 0.54, p < 0.01) and uridine (r = − 0.58, p < 0.05; r = − 0.50, p < 0.01) in PIN and PCa groups, respectively] and metabolites that were significantly different in PCa patients with Gleason score < 7 and ≥ 7 [i.e. arachidonic acid, median (P25–P75) = 883.0 (619.8–956.4) versus 570.8 (505.6–651.8), respectively (p < 0.01)].

Conclusions

This human plasma metabolomic assessment contributes to the understanding of the unique metabolic features exhibited in PIN and PCa and provides a list of metabolites that can have the potential to be used as biomarkers for early detection of disease progression and management.

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Abbreviations

PIN:

Prostatic intraepithelial neoplasia

PCa:

Prostate cancer

GC–MS:

Gas chromatography/mass spectrometry

UPLC-TQ/MS:

Ultra performance liquid chromatography-triple quadrupole/mass spectrometry

PSA:

Prostate-specific antigen

MSTFA:

N-Methyl-N-trimethylsilyltrifluoroacetamide

BSA:

Bovine serum albumin

IQR:

Interquartile range

FDR:

False discovery rate

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Funding

This study was funded by Project 5-100 Sechenov University Grant.

Author information

Author notes

  1. Pavel A. Markin and Alex Brito have contributed equally to this work.

Authors and Affiliations

  1. Laboratory of Pharmacokinetics and Metabolomic Analysis, Institute of Translational Medicine and Biotechnology, I.M. Sechenov First Moscow State Medical University, 2-4 Bolshaya Pirogovskaya St., Moscow, Russia, 119991

    Pavel A. Markin, Alex Brito, Natalia Moskaleva & Svetlana A. Appolonova

  2. PhD Program in Nanosciences and Advanced Technologies, University of Verona, Verona, Italy

    Pavel A. Markin

  3. University Clinical Hospital, I.M. Sechenov First Moscow State Medical University, Moscow, Russia

    Ekaterina V. Lartsova & Vasily Y. Mikhajlov

  4. Research Institute of Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia

    Yevgeny V. Shpot, Natalia V. Potoldykova & Dimitry V. Enikeev

  5. Department of Pathological Anatomy, I.M. Sechenov First Moscow State Medical University, Moscow, Russia

    Yulia V. Lerner

  6. Department of Food Science and Nutrition, California Polytechnic State University, San Luis Obispo, CA, USA

    Michael R. La Frano

  7. Center for Health Research, California Polytechnic State University, San Luis Obispo, CA, USA

    Michael R. La Frano

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  1. Pavel A. Markin
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Contributions

The author responsibilities—PAM participated in sample collection, conducted biochemical analyses, performed statistical analyses, interpreted biological and clinical information, and provided input to the manuscript. AB conceptualized the study, performed statistical analyses, interpreted biological and clinical information, and wrote the manuscript. NM conducted biochemical analyses, interpreted biological information and provided input to the manuscript. MRL interpreted metabolic information and provided input to the manuscript. EVL, YVS, YVL, VYM, NVP, DVE and AVL were part of patient recruitment, sample collection, medical history and clinical procedures. SAA conceived the main study and supervised the study. SAA and AB have final responsibility for all parts of this research.

Corresponding authors

Correspondence to Alex Brito or Svetlana A. Appolonova.

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Conflict of interest

None of the authors have a conflict of interest to declare.

Ethical approval

This research was approved by the Ethics Committee at the I.M Sechenov First Moscow State Medical University, Moscow, Russia. Written signed informed consent was obtained from each volunteer before entry into the study. The study was performed in conformity with the ethical principles for medical research involving humans stated in the Declaration of Helsinki.

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11306_2020_1694_MOESM1_ESM.docx

Supplementary Material: Supplementary table 1: Flow rates for separation of purines and pyrimidines. Supplementary table 2: Non-significant comparison across groups untargeted metabolomics. Supplementary table 3: Non-significant comparison across groups targeted metabolomics. Supplementary table 4: Enrichment analysis control group versus PIN. Supplementary table 5: Enrichment analysis control group versus PCa. Supplementary table 6: Spearman correlations untargeted and targeted metabolomics versus PSA across all groups. Supplementary table 7: Non-significant comparisons untargeted metabolomics according to Gleason score in the PCa group. Supplementary table 8: Non-significant comparisons targeted metabolomics according to Gleason score in the PCa group. Supplementary file1 (DOCX 69 kb)

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Markin, P.A., Brito, A., Moskaleva, N. et al. Plasma metabolomic profile in prostatic intraepithelial neoplasia and prostate cancer and associations with the prostate-specific antigen and the Gleason score. Metabolomics 16, 74 (2020). https://doi.org/10.1007/s11306-020-01694-y

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